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Dictionary of Applied Machine Learning

Official registry Search and web

Look up, search and cross-reference machine-learning terms from dictionaryofml.org.

Source code Website Documentation

Install

Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).

Remote (streamable-http)
Claude Code 
claude mcp add --transport http dictionary-of-applied-machine-learning 'https://dictionaryofml.org/mcp'
JSON configuration (Claude Desktop, Cursor, VS Code) 
{
    "mcpServers": {
        "dictionary-of-applied-machine-learning": {
            "type": "http",
            "url": "https://dictionaryofml.org/mcp"
        }
    }
}

Documentation

From the project's README on GitHub, refreshed weekly. Links open on GitHub.

Contents
  1. Dictionary of Applied Machine Learning — companion repository
  2. Provenance and disclaimer
  3. MCP server
  4. Citing
  5. License

Dictionary of Applied Machine Learning — companion repository

Companion code for the Dictionary of Applied Machine Learning (course edition, CC BY 4.0): 107 machine-learning terms, each defined precisely and cross-referenced, with citations, a typeset PDF, and a Python demo that recomputes what the entry states.

DirectoryContents
notebooks/The per-term Python demos as Jupyter notebooks — each opens in Colab with one click from its demo page
mldict/mldict.sty: the dictionary's notation as a LaTeX package (\usepackage{mldict})
mcp/An MCP server exposing the dictionary to AI assistants (Claude Code, VS Code Copilot, …)

The notebooks and mldict.sty are generated from the dictionary's source; edits belong there, not here. The dictionary itself — definitions, symbol list, per-term PDFs — lives at dictionaryofml.org; the full content is also machine-readable as terms.json and indexed for LLM crawlers in llms.txt.

Provenance and disclaimer

The source code in this repository (demo notebooks, LaTeX package, MCP server) was created with the help of large language models (LLMs), under review by the author. It is provided as is, without warranty of any kind: use at your own risk and verify results independently before relying on them.

Basic checks are applied to the Python demos before release:

  • each demo runs its own check() assertions on the quantities it computes, with fixed random seeds for reproducibility;
  • ruff check --select F (correctness rules only: undefined and unused names);
  • bandit, restricted to the exec/eval/shell-injection checks (B102, B307, B602, B605) — the one deliberate exception is the llm demo, whose subject is an LLM wrapper executing emitted code;
  • project-specific linters for figure style and for keeping a demo's prose within the concepts its dictionary entry introduces.

These are screens, not proofs of correctness.

The demos import two third-party packages, numpy and matplotlib (both preinstalled on Colab); the source repository pins their exact versions, since the committed figure data is byte-reproducible only under the pinned pair.

MCP server

pip install -r mcp/requirements.txt
claude mcp add --scope user dictionaryofml -- python /path/to/mcp/server.py

Tools: list_all_terms, lookup_term, search_terms, get_related_terms. Content is fetched from the site's terms.json and cached for a day.

Citing

@misc{dictml,
  author = {Jung, Alexander and Olioumtsevits, Konstantina and Schnoor, Ekkehard},
  title = {Dictionary of Applied Machine Learning (course edition)},
  doi = {10.5281/zenodo.21569296},
  note = {ISBN 978-952-64-3013-3, CC BY 4.0},
  url = {https://dictionaryofml.org}
}

Each term page carries its own "Cite this entry" BibTeX block. This repository is a course-edition companion, distinct from the copyrighted Springer Dictionary of Applied Machine Learning.

License

CC BY 4.0. Maintained by Alexander Jung, Aalto University; corrections and suggestions are welcome at the address on dictionaryofml.org.

Frequently asked questions

What is Dictionary of Applied Machine Learning?

Look up, search and cross-reference machine-learning terms from dictionaryofml.org.

How do I install Dictionary of Applied Machine Learning?

It runs as a remote server. In Claude Code: claude mcp add --transport http dictionary-of-applied-machine-learning 'https://dictionaryofml.org/mcp'. For other clients, paste the JSON configuration from this page into their MCP settings.

Does Dictionary of Applied Machine Learning need an API key?

Its registry entry lists no required key or secret. Some features may still need an account with the service it connects to.

Is Dictionary of Applied Machine Learning open source?

Its code is public on GitHub, but the repository does not declare a standard license.

Who maintains Dictionary of Applied Machine Learning?

It is published by alexjungaalto. AI.tn lists it but does not maintain or endorse it.

From the official MCP Registry. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.